Lifeboat Foundation

1,271 likes, — artificialintelligencenews.in on November 22, 2024: According to former Google CEO Eric Schmidt, the tech industry anticipates that within the next five years, AI systems will be able to write and improve their code. This means AI will soon be capable of analyzing and enhancing its programming, setting off a recursive process that could dramatically accelerate development.

Schmidt suggests that by around 2030–2032, we might see a single AI system that can match 80–90% of the expertise of top specialists across various fields—whether that’s physics, chemistry, art, or more. Such a system would, in effect, be smarter than any human, as no one person can excel in all these disciplines at once. In short, Schmidt believes we are approaching a future where AI could possess intellectual versatility that surpasses any individual human’s abilities.

The first casualties of generative AI offer clues as to when a business may be strengthened by the technology—and when it will be upended. Examining them suggests three lessons for firms.

Dysolve, the first artificial intelligence-powered platform for dissolving dyslexia and associated learning disabilities, is paving the way for a new treatment approach.

Dyslexia is a neurodevelopmental learning disorder that makes it challenging for children and adults to read, write, and spell. The condition affects one out of every five people and represents 80% to 90% of those with learning disabilities.

Continue reading “AI-Powered Software Offers Breakthrough for Treating Dyslexia” »

Scientists at the National Institutes of Health (NIH) have uncovered a brain circuit in primates that rapidly detects faces. The findings help not only explain how primates sense and recognize faces, but could also have implications for understanding conditions such as autism, where face detection and recognition are often impaired from early childhood.

The newly discovered circuit first engages an evolutionarily ancient part of the brain called the superior colliculus, which can then trigger the eyes and head to turn for a better look. This better view enables different brain areas in the temporal cortex to engage in more complex facial recognition. The study was published in the journal Neuron.

“Quick recognition of faces is a key skill in humans and other primates,” said Richard Krauzlis, Ph.D., of NIH’s National Eye Institute (NEI) and senior author of the study.

Researchers have explained how the regularly structured topographic maps in the visual cortex of the brain could arise spontaneously to efficiently process visual information. This research provides a new framework for understanding functional architectures in the visual cortex during early developmental stages.

A KAIST research team led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering has demonstrated that the orthogonal organization of retinal mosaics in the periphery is mirrored onto the primary visual cortex and initiates the clustered topography of higher visual areas in the brain.

This new finding provides advanced insights into the mechanisms underlying a biological strategy of brain circuitry for the efficient tiling of sensory modules. The study was published in Cell Reports on January 5.

Generative AI could saddle the planet with heaps more hazardous waste.

By Saima S. Iqbal

Every time generative artificial intelligence drafts an e-mail or conjures up an image, the planet pays for it. Making two images can consume as much energy as charging a smartphone; a single exchange with ChatGPT can heat up a server so much that it requires a bottle’s worth of water to cool. At scale, these costs soar. By 2027, the global AI sector could annually consume as much electricity as the Netherlands, according to one recent estimate. And a new study in Nature Computational Science identifies another concern: AI’s outsize contribution to the world’s mounting heap of electronic waste. The study found that generative AI applications alone could add 1.2 million to five million metric tons of this hazardous trash to the planet by 2030, depending on how quickly the industry grows.

AI-human collaboration could possibly achieve superhuman greatness in mathematics.

By Conor Purcell

Mathematicians explore ideas by proposing conjectures and proving them with theorems. For centuries, they built these proofs line by careful line, and most math researchers still work like that today. But artificial intelligence is poised to fundamentally change this process. AI assistants nicknamed “co-pilots” are beginning to help mathematicians develop proofs—with a real possibility this will one day let humans answer some problems that are currently beyond our mind’s reach.

NYU Langone performs the world’s first fully robotic double lung transplant, marking a breakthrough in minimally invasive surgical care.

MIT researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. This could enable the leverage of reinforcement learning across a wide range of applications.